Monitoring psychophysiological and neuromuscular parameters in beach volleyball high-performance athletes

Monitoramento de parâmetros psicofisiológicos e neuromusculares em atletas de voleibol de praia de alto rendimento

Monitorización de parámetros psicofisiológicos e neuromusculares en atletas de voley playa de alto rendimiento

ABSTRACT

The aim of the study was to monitor and compare changes in psychophysiological and neuromuscular parameters in the training period (TP), during and after competition between blockers and defenders in high-performance beach volleyball (BV). Eight male high-performance BV players, participated in this study. The study monitored heart rate variability (HRV), countermoviment jump (CMJ), training impulse (TRIMP), monotony, strain, total weekly training load (TWTL) and daily training load (DTL). There was no significant difference in HRV, monotony, and CMJ between TP vs. during and after competition (p> 0.05). However, results observed showed that TRIMP, TWTL, DTL and Strain in the TP was significantly higher than the competition and post-competition (p< 0.05). There was no significant difference in the CMJ and psychophysiological parameters between defenders and blockers players (p< 0.05). We conclude that the changes in psychophysiological and CMJ parameters were similar between blockers and defenders and the training loads were well distributed with increases in the first two weeks before the competition and reduced training loads during and after the competition.

Keywords:
Heart rate variability; Vertical jump; Rating of perceived exertion; Sports activities; Sand sports

RESUMO

O objetivo do estudo foi monitorar e comparar as alterações nos parâmetros psicofisiológicos e neuromusculares no período de treinamento (PT), durante e após a competição entre atletas de vôlei de praia (VP) bloqueadores e defensores de alto rendimento. Oito atletas homens de vôlei de praia de alto rendimento, participaram do estudo. O estudo monitorou a variabilidade da frequência cardíaca (VFC), o salto contramovimento (CMJ), o impulso de treinamento (TRIMP), monotonia, strain, carga total de treinamento semanal (CTTS) e a carga diária de treinamento (CDT). Não houve diferença significativa na VFC, monotonia e CMJ entre PT vs. durante e após a competição (p> 0.05). No entanto, foi observado que TRIMP, CTTS, CDT e Strain no PT foi significativamente maior do que no período de competição e pós-competição (p< 0.05). Não houve diferença significativa no desempenho do CMJ e nos parâmetros psicofisiológicos entre atletas defensores e bloqueadores (p< 0.05). Concluímos que as alterações nos parâmetros psicofisiológicos e do CMJ foram semelhantes entre bloqueadores e defensores e que as cargas de treinamento foram bem distribuídas com aumentos nas duas primeiras semanas antes da competição e redução das cargas de treinamento durante e após a competição.

Palavras-chave:
Variabilidade da frequência cardíaca; Salto vertical; Percepção subjetiva de esforço; Atividades esportivas; Esportes de areia

RESUMEN

El objetivo del estudio fue monitorizar y comparar los cambios en los parámetros psicofisiológicos y neuromusculares en el periodo de entrenamiento (PE), durante y después de la competición entre bloqueadores y defensores de voley playa (VP) de alto rendimento. Ocho jugadores de voley playa de alto rendimiento masculinos, participaron en el estudio. El estudio monitorizó la variabilidad de la frecuencia cardiaca (VFC), salto contramovimiento (CMJ), impulso de entrenamiento (TRIMP), monotonía, tensión, carga de entrenamiento semanal total (CEST) y la carga de entrenamiento diaria (CED). No hubo diferencias significativas en la VFC, monotonía y CMJ entre el PE vs. durante y después de la competición (p> 0.05). Sin embargo, se observó que TRIMP, CEST, CED y Strain en el PE fueron significativamente mayores que en el periodo de competición y post-competición (p< 0.05). No hubo diferencias significativas en el rendimiento CMJ y los parámetros psicofisiológicos entre los atletas defensores y bloqueadores (p< 0.05). Concluimos que los cambios en los parámetros psicofisiológicos y en el CMJ fueron similares entre bloqueadores y defensores y que las cargas de entrenamiento estuvieron bien distribuidas con aumentos en las dos primeras semanas antes de la competición y disminuciones en las cargas de entrenamiento durante y después de la competición.

Palabras clave:
Variabilidad de la frecuencia cardiaca; Salto vertical; Percepción subjetiva del esfuerzo; Actividades deportivas; Deportes de arena

INTRODUCTION

Beach volleyball (BV) is a team sport characterized by its intermittent nature, ranging randomly from brief periods of maximum or near-maximum activity to more extended periods of moderate and low intensity activity (Magalhães et al., 2011). During a beach volleyball match, athletes perform short and fast displacements and many jumps (Magalhães et al., 2011; Nunes et al., 2020), requiring good speed and muscle strength, considering that they are abilities that influence success in this sport (Oliveira et al., 2018). Adequate training loads must be applied so that the athletes present satisfactory physical performance to meet the demands requested during competitions.

Therefore, the training load, considered the product of the training volume and intensity (Impellizzeri et al., 2005), is crucial in developing and prescribing an athlete's training (Wood et al., 2005). Training load is divided into internal and external loads. The external load is associated with applying external stimuli and can be expressed by the number of sets/repetitions, intervals, and effort intensities, among others (Wallace et al., 2009). On the other hand, the internal load can be defined as adaptations induced by training resulting from the body's stress level (Impellizzeri et al., 2005).

Therefore, the coaching staff needs to understand if the applied external stimuli during training sessions are adequate for the athlete and if these loads are similar to the stimuli imposed during competition. Thus, the training process's success depends on accurate internal load monitoring. Several parameters can be used to assess the internal load, such: as the level of perceived exertion (Borg and Borg, 2002), mood states, sleep quality, heart rate variability (HRV), lactate concentration (Halson, 2014; Nakamura et al, 2020), training impulse (TRIMP), jump height (Nakamura et al., 2020) among others.

It is noticed in the literature that some studies investigated the monitoring of the training load in collective sports modalities such as Rugby (Nakamura et al., 2017), judo (Morales et al., 2014), basketball, and soccer (Esco and Flatt, 2014; Flatt and Esco, 2016), futsal (Pereira et al., 2016; Nakamura et al., 2016), Beach volleyball (Nakamura et al., 2020), and in the individual sports. On beach volleyball, Oliveira et al. (2018) monitored in a feminine beach volleyball pair the internal training load (ITL), total weekly training load (TWTL), monotony and strain that were obtained through the session rating of perceived exertion (session-RPE) for three training mesocycles (10 weeks) during a period that preceded the participation of these athletes in the 2016 Olympic Games and these authors observed that ITL magnitude increased from the first to the third mesocycle, in both players.

Additionally, in the study by Nunes et al. (2020) the authors monitored the training load of a female beach volleyball team in national and international competitions. In this study, the authors found that blocker athlete and international competitions presented higher physical demands than their pairs during the game, suggesting that the position and the level of competition are influenced by game demands. In the study by Nakamura et al. (2022) these authors monitoring changes in heart rate variability and perception of well-being in under-17 and adult athletes after a day of the beach volleyball tournament, and observed that the log-transformed root mean square of sucessive R-R intervals (lnRMSSD) index was able to discriminate the U17 and senior beach volleyball players, and maintaining high vagally related HRV indices is an important response to beach volleyball training and competition.

Given the evidence, no study has monitored changes in psychophysiological (Heart rate variability, impulse training, monotony, strain, total weekly training load) and neuromuscular (countermovement jump) parameters of beach volleyball athletes in the preparation period before the competition, in the week of competition and after the competition, it is necessary to investigate the training load in the beach volleyball, since load monitoring can be used to better optimize training, which can consequently reduce the risk of injuries and overtraining syndrome (Foster, 1998; Taha and Thomas, 2003) as well as the possibility of positively maximizing performance, whether in training or competition.

In addition, a comparative analysis of the training load in beach volleyball athlete’s blocker and defender is essential since the responses of the internal load between the positions can also be different, as shown by another study in beach volleyball (Nunes et al., 2020). There is already evidence that the blocker, for example, can perform more actions at high intensity, given that they block each opponent’s attack compared to the position of the defender, who performs fewer displacements to position himself to recover the ball (Oliveira et al., 2018; Medeiros et al., 2014). Therefore, the aim of the study was to monitor and compare changes in psychophysiological and neuromuscular parameters in the training period (TP), during and after competition between blockers and defenders athletes professional beach volleyball. This study can support beach volleyball’s current physical training programs, allowing coaches and physical trainers to elaborate more efficiently on team planning.

MATERIALS AND METHODS

Participants

Eight male professional beach volleyball athletes (Blocker – age: 24.2 ± 3.7 years; height: 192.7 ± 12.0 cm; body mass: 82.5 ± 13.8 kg; body fat: 13.0 ± 2.0%; muscle mass: 67.8 ± 12.2 kg; body fat mass: 10.6 ± 1.7 kg and Defender – age: 22.0 ± 4.5 years; height: 188.0 ± 6.7 cm; body mass: 88.3 ± 8.7 kg; body fat: 14.7 ± 3.8% muscle mass: 70.7 ± 7.6 kg; body fat mass: 13.0 ± 3.4 kg) who compete in national and international championships voluntarily participated in the study. To be included in the study, the athletes had to be between 18 and 30 years old, have no musculoskeletal injuries that would prevent them from training or competing, be registered with the Brazilian Volleyball Confederation and have taken part in the last season of the Brazilian or world beach volleyball circuit. This study was performed in accordance with the Declaration of Helsinki and approved by the institutional review board of the Centro universitário de João Pessoa, protocol 3,638.667.

Study design

The present study lasted four weeks. The first two weeks of the study correspond to the athletes’ training period before the competition. The 3rd week of the study corresponds to the period in which the athletes were in competition and the 4th week corresponds to the post-competition period. Over the weeks, HRV, CMJ, TRIMP, and rating of perceived exertion (RPE) were monitored. Before the training sessions and games, the athletes took heart rate variability measurements, did a volleyball-specific warm-up for 10 minutes and then performed the vertical jump test. Immediately after the end of the training session or game, the training impulse (TRIMP) was calculated, and then the vertical jump test was performed, while the RPE scale was used after 15 minutes of each training session or game.

Anthropometry and body composition

The body height of beach volleyball athletes was measured using a Sanny® stadiometer. At the same time, body mass, body mass index, and fat percentage were evaluated using the InBody 570 octopolar bioimpedance, complying with the procedures specified in the literature (Pitanga et al., 2012). The athletes received instructions to carry out this evaluation, such as a) fasting; b) do not consume alcoholic beverages within 48 hours of the exam; c) do not perform intense physical exercises 12 hours before the evaluation; d) do not perform the exam in the presence of a feverish or dehydrated state; e) do not use metallic objects during the exam; (f) not drinking coffee; and (g) performing the assessment in a bathing suit or underwear (Pitanga et al., 2012).

Rating of perceived exertion (RPE)

The RPE was measured using the Borg CR100 scale from 0 to 100 points (Fanchini et al., 2016). Athletes were asked about their perceived exertion within 15 minutes after each training session or game (Uchida et al., 2014). For RPE session analysis, the number associated with the descriptor was multiplied by the total duration of the game and divided by 10 (to provide values comparable to CR10) (Fanchini et al., 2016). The session or game duration was recorded using a digital stopwatch (HS-3V-1R, Casio, USA) and 15 minutes after the end of the session or game the athlete was asked to answer the following question: “How was your workout?” using the RPE scale Borg's CR-100 scale (Fanchini et al., 2016). The training load of all training sessions was estimated, in arbitrary units (AU), by multiplying the RPE for the entire training session by the length of each training session or game in minutes (RPE-session) (Foster et al., 2001).

On days that featured two training sessions, the training load (TL) of the sessions was summed, obtaining the daily TL (DTL). In each microcycle (7 days), the total weekly training load (TWTL) was calculated by adding the DTLs. In addition, the monotony and training strain indexes proposed by Foster et al. (2001) were calculated. Monotony indicates the load variability between training sessions, in which high scores may contribute to negative training adaptations (Foster et al., 2001; Rodríguez-Marroyo et al., 2009). Training monotony was calculated using the following formula: Monotony= weekly mean TL/SD, where weekly mean TL is the average daily TL during the week and SD is the standard deviation of the daily TL calculated over a week. In turn, strain is usually related to the level of adaptation to training, in which periods with high load associated with monotony may increase the incidence of infectious diseases and injuries. This index is equal to the multiplication of the TWTL and the monotony scores.

Heart rate variability (HRV)

Resting HRV was recorded by calculating R-R intervals using a portable heart rate monitor (Firstbeat®, Oy, Finlândia). Heart rate variability was measured in the morning, before the first training session or game on four different days during the training weeks, during and after the competition week. Before starting the study, participants were instructed to rest for 10 minutes in a sitting position, with the final 5 minutes used as the analysis criterion for the resting HRV (Soares-Caldeira et al., 2014). Time domain measures included the square root of the mean squared differences of successive RR intervals (RMSSD; parasympathetic index) and standard deviation of the R-R intervals (SDNN; sympathetic-parasympathetic index). Due to the skewed nature of HRV recordings, data were log-transformed by means of natural logarithm (ln) before analyzing each HRV index (Nakamura et al., 2022). In the present study, was used the log-transformed root mean square of successive R-R intervals (lnRMSSD), that is a vagal-related heart rate variability index that has become a promising method for monitoring individual adaptation to training when measured during resting or post-exercise conditions (Esco and Flatt, 2014).

Trimp

Training impulse (TRIMP) was measured using the Bluetooth Smart Sensor strap from Firstbeat Technologies (Firstbeat®, Oy, Finland) from the record of the average percentage of reserve heart rate (HRr) maintained during a training session or competition, using the two equations proposed by Banister and Calvert (1980). This equation assumes that the training load can be expressed by multiplying exercise intensity and duration.

$$TRIMP=durationxHRrx0.64xex{p}^{\mathrm{1.92.}HRr}$$ (1)

Assessment of counter movement jump

Data were collected using My jump 2^® mobile application, which was designed and validated to perform vertical and horizontal jumps and allows the calculation of the height of jumps (ICC = 0.997; p < 0.001) (Balsalobre-Fernández et al., 2015). The counter movement jump (CMJ) was performed to obtain these data (Rodrigues and Marins, 2011). Three jumps were performed in each test with 60 seconds rest and the jump mean was later calculated for analysis. During the CMJ, the subject was instructed to rest his hands on his hips while performing a downward movement to reach about 90° of knee flexion, followed by a maximal vertical jump (Komi and Bosco, 1978). All subjects were instructed to keep their knees straight during the flight phase of the jump, and to land in an upright position in order to negate the possibility of overestimation of jump height. The reliability for the CMJ test was Coefficient of variation (CV): 8.60%.

Data collection procedures

Training period

Beach volleyball athletes were monitored in the physical and tactical-technical training sessions that took place two weeks before the stage of the Brazilian Circuit that took place in the city of João Pessoa. The training period was set for two weeks before the competition (weeks 1 and 2). The tactical-technical training sessions lasted approximately 2 hours and the physical training sessions lasted 1 hour. From the 1st to the 5th day of training, upon waking up, the HRV was measured using a Firstbeat heart rate monitor (Firstbeat®, Oy, Finland). Upon arriving at the training center before the start of the training session, the athletes performed the daily warm-up and then the CMJ test.

During the entire training, the athletes were monitored through the heart rate monitoring strap; at the end of the training session, the belt was removed, and the TRIMP data were stored. After 15 minutes, was presented the CR-100 scale to the athletes individually to respond to their RPE after the training session. Finally, the athletes performed three more vertical jumps. During the first week before of the competition, athletes carried out a mean of nine tactical-technical training sessions and two physical training sessions, and during the second week before of the competition, athletes carried out a mean of eight tactical-technical training sessions and three physical training sessions.

Competition period

During the competition week, when waking up, the HRV was measured. Arriving at the place of the games before each game, the athletes performed a warm-up and then three CMJs. During the entire game, the athletes were monitored by heart rate. At the end of the game, the belt was removed, and the TRIMP data were stored; 15 minutes after of the games, the RPE was answered, and three more CMJs were performed. During the week of the competition, athletes carried out a mean of three tactical-technical training sessions and one physical training sessions. The tactical-technical training sessions lasted approximately 2 hours and the physical training sessions lasted 1 hour. In the competition, athletes participated in mean of 4 games. The competition period was characterized as week 3.

Post-competition period

From the 1st to the 4th day of training, the athletes, upon waking up, measured the HRV. Upon arriving at the training center, before the start of the training session, the athletes performed the daily warm-up and then the CMJ test. Throughout the training, the athletes were monitored by heart rate. At the end of the training session, the belt was removed, and the TRIMP data were stored. After 15 minutes, was presented the CR-100 scale to the athletes individually to respond to their RPE after the training session. Finally, the athletes performed three more vertical jumps. During the week of the post-competition, athletes carried out a mean of three tactical-technical training sessions and two physical training sessions. The tactical and technical training sessions lasted approximately 2 hours and the physical training sessions lasted 1 hour. The post-competition period was characterized as week 4.

Statistical analysis

All statistical procedures were performed using SPSS (SPSS 21; IBM, Inc., NY). Normality of data’s distribuition were confirmed using the Shapiro-Wilk. Two-way mixed model analyses of variance (ANOVAs) (group [2= blocker x defender] X time [3= training x competition x post competition]) were used to test all main effects and interactions. Post hoc Bonferroni procedure was used when performing all pairwise comparisons. The Greenhouse‐Geisser correction was used whenever the sphericity assumption was not met. For each dependent variable, the value of the magnitude of the differences (F), significance (p) and the estimated effect size were presented using cut-off points of 0.2; 0.5 and 0.8 to represent a small, medium and large effect size, respectively (Cohen, 1988). The level of significance was set at p ≤ 0.05 and data are presented as mean ± SD.

RESULTS

In the comparative analysis of jump height CMJ, there was no significant difference in the group x time (F = 0.326; p = 0.664; ${\eta }_G^2$= 0.026), in the group (F = 0.193; p = 0.762; ${\eta }_G^2$= 0.016) and in time (F = 1.18; p = 0.324; ${\eta }_G^2$= 0.090), as seen in Figure 1.

Figure 1
Mean results of maximal vertical countermovement jump height (cm) in beach volleyball athletes during training, competition, and after the competition. Legend: A = before the training/game – B = After the training/game.

Analyses revealed that no significant differences existed between blocker vs. defender at LnRMSSD (F = 2.58; p = 0.138; ${\eta }_G^2$= 0.301), TRIMP (F = 0.732; p = 0.474; ${\eta }_G^2$= 0.109), total weekly training load (F = 0.033; p = 0.895; ${\eta }_G^2$= 0.005), daily training load (F = 0.029; p = 0.903; ${\eta }_G^2$= 0.005), monotony (F = 0.334; p = 0.600; ${\eta }_G^2$= 0.053) and strain (F = 0.021; p = 0.923; ${\eta }_G^2$= 0.004). In the comparisons across time points within each given group, post hoc analysis, it was found that in the group of defensive athletes, there was a significant reduction in the TRIMP of the training moment vs. post-competition (p = 0.021; Δ% = -45.4 -27.8; ES = -2.1). In the group of blocking athletes, there was a significant reduction in the TRIMP of the training moment vs. competition (p = 0.043; Δ% = -29.8; ES = -1.5) and training vs. post-competition (p = 0.012; Δ% = -50.7; ES = -2.6), as seen in Table 1.

Table 1
Monitoring physicophysiological parameters of beach volleyball players on the training, competition and post competition.

Parameter Physicophysiological	Defender			Blocker
	Training	Competition	Post-Competition	Training	Competition	Post-Competition
LnRMSSD (m.s)	4.2 ± 0.2	4.4 ± 0.1	4.6 ± 0.1	3.8 ± 0.1	4.0 ± 0.2	4.6 ± 0.2
Trimp	839.2 ± 175.2	795.7 ± 226.2	457.7 ± 215.7*	865.5 ± 167.8	607.2 ± 140.5*	426.2 ± 113.2*
TWTL (a.u)	3993.3 ± 1621.8	2004.5 ± 643.3*	437.7 ± 207.2*	3734.3 ± 1591.8	1922.7 ± 549.6*	418.3 ± 108.2*
DTL (a.u)	570.2 ± 231.7	286.2 ± 91.9*	65.3 ± 30.8*	535.4 ± 224.3	275.0 ± 80.3*	60.0 ± 16.1*
Monotony (a.u)	1.07±0.1	1.04±0.3	1.08±0.8	1.08±0.1	1.09±0.2	1.11±0.9
Strain (a.u)	4369.5 ± 2192	2239 ± 1226.7*	1022 ± 576.9*	4179.3 ± 2085.2	2168.5 ± 1121.9*	676.4 ± 336.2*

• Legend: TWTL- Total weekly training load; DTL- Daily training load; a.u- arbitrary units; LnRMSSD= log- transformed root mean square of sucessive R-R intervals.
• ^*
  = different significantly at the moment training.

In the analysis for the total weekly training load, post hoc analysis, it was found that in the group of defending athletes there was a significant reduction in the TWTL of the moment training vs. competition (p = 0.024; Δ%= -49.8; ES= -1.2; high) and training vs. post competition (p = 0.006; Δ% = -88.5; ES = -2.1; high). In the group of blocking athletes, there was a reduction in the TWTL of the moment training vs. competition (p = 0.034; Δ%= -48.8; ES= -1.1; high) and training vs. post competition (p = 0.008; Δ% = -88.5; ES = -2.0; high).

In the analysis for the daily training load, post hoc analysis, it was found in the group of defending athletes, there was a significant reduction in the DTL at the moment training vs. competition (p = 0.023; Δ% = -49.8; ES = -1.2; high) and training vs. post-competition (p = 0.006; Δ% = -88.5; ES = -2.1; high). In the group of blocking athletes, there was a reduction in the DTL at the moment training vs. in competition (p = 0.031; Δ% = -48.6; ES = -1.1) and training vs. post-competition (p = 0.008; Δ% = -88.6; ES = -2.1), as seen in Table 1.

In the analysis for the Strain, post hoc analysis, it was found that in the group of defensive athletes there was a significant reduction of the Strain in the moment training vs. competition (p = 0.021; Δ%= -40.4; ES = -0.9) and training vs. post competition (p = 0.039; Δ% = -76.6; ES = -1.5). In the group of blocking athletes, there was a reduction in the Strain of the moment training vs. competition (p = 0.027; Δ% = -48.1; ES = 0.96) and training vs. post-competition moment (p = 0.033; Δ% = -83.8; ES = -1.6), as seen in Table 1.

DISCUSSION

The aim of the study was to monitor and compare changes in psychophysiological and neuromuscular parameters in the training period (TP), during and after competition between blockers and defenders athletes professional beach volleyball. The main findings of the study were: a) there was no significant difference in HRV, monotony, and jump height between training, competition, and post-competition periods; b) in the variables TRIMP, TWTL, DTL and Strain of beach volleyball athletes, the training period was significantly higher than the competition and post-competition moments; c) there was no significant difference in the variables HRV, monotony, jump height CMJ, TRIMP, TWTL, DTL, and Strain between defenders and blockers beach volleyball players.

Resting HRV has been used to indicate positive and negative adaptations to training loads (Buchheit, 2014). In the present study, no significant changes were observed for this measure in beach volleyball blockers and defenders between training, competition, and post-competition periods. It should be noted that even with changes in loads, with the highest at the time of training, there were no significant fluctuations in LnRMSSD between periods. This can be explained by the heightened ability to maintain cardiac autonomic responses, as seen in Rugby Sevens athletes (Flatt and Howells, 2019) and in adult beach volleyball athletes in moments of competition (Nakamura et al., 2022).

It seems that the loads imposed during the study were adequate since significant increases in training loads can generate insufficient recovery (Nakamura et al., 2017) and consequently, a decrease in HRV rates, which can indicate overtraining and exhaustion. In addition, it can be seen that despite the short-term application of training loads, there was a percentage increase of 4.76% of LnRMSSD in athletes defending the training moment for the competition and 9.52% of the training moment for post-competition. As too 5.2% increase in LnRMSSD in blocker athlete from training period to competition and 21% from training period to post-competition. These magnitudes may show positive adaptations to training with increased parasympathetic tone at rest (Buchheit, 2014) in these athletes.

Another point to be highlighted is that, at the time of competition, there was no reduction in HRV, which could be expected. For, in team sports such as football, players submitted to 60 minutes of play showed reductions in HRV, demonstrating a possible acute state of fatigue, with recovery up to 72 hours (Muñoz-López et al., 2021). The beach volleyball athletes in our study, even with the loads imposed during competition days, submitted to two or three games a day, did not show reductions in HRV. These data are similar to previous studies that showed a decrease only for beach volleyball youth athletes (Nakamura et al., 2020). In the study by Nakamura et al. (2020), it was demonstrated that under-17 players experienced a more significant decrease in HRV compared to adult athletes. The authors explained that players with higher LnRMSSD values ​​could cope with highly demanding physiological stress than their peers with less vagal modulation (Buchheit, 2014).

The internal load variables, such as TRIMP, total accumulated load value, weekly daily average, and Strain, showed that beach volleyball athletes were submitted to a higher training load demand during the training period concerning the workloads in the competition and post-competition. The study researchers had no interference in planning and programming, only collection and analysis related to load monitoring. Furthermore, the technical committee did not receive any feedback on the data collected during the study. All the planning, programming, and organization were under the responsibility of the technical committee itself. This is important to highlight as the study data reveal the experience of the technical committee in the programming and distribution of loads since research suggests that adopting high internal training loads, primarily related to the increase in volume in moments before competitions, can optimize the performance in competitive periods (Aoki et al., 2017; Moreira et al., 2010).

Usually, the beach volleyball season has a competitive calendar throughout the year, characterizing this modality as a collective sport with a congested calendar (Nassis et al., 2020). In our results, the competitive mesocycle analyzed shows a load increase in the first two weeks before the competition week and a significant reduction in the following weeks (competition and post-competition). The literature affirmative that in team sports, there is no defined moment for load accumulation, which may occur in the regular season, with emphasis on a load reduction close to competitive events in an attempt to recover sufficiently for the games (Boullosa et al., 2020). Furthermore, the similar responses between the internal load measures (TRIMP and RPE) suggest that these markers represent a similar construct and can be used individually or together.

The literature on beach volleyball shows that blocking athletes exhibit greater physical demands in the game (Nunes et al., 2020). These are high-intensity actions such as blocking, displacements with sprints to the net, and the number of jumps that expose blockers to greater loads than defenders (Oliveira et al., 2018; Medeiros et al., 2014). However, in our results, the internal load response between defenders and blockers was similar during training, in competition, and after the competition. When analyzed by RPE, the data shows similar declines across roles in the moments. This can be explained by the fact that RPE is strongly influenced by session duration (~60-70%), while a smaller proportion is explained by session intensity (~30%) (Weaving et al., 2020). When analyzed from the perspective of TRIMP, especially for defenders, training’s TRIMP is similar to the competition. This data is difficult to explain because it is multifaceted. The game’s physical demands may have been more significant for the defender due to tactical characteristics such as the defender may have received more balls from the opponent’s serve and, in turn, needs to receive (first touch) and jump to attack (third touch). While the blocking athlete in the typical game sequence only needs to set (second touch).

Regarding the monotony index, in the present study, it was found that at the time of training, competition, and post-competition, these values were below 2.0 AU. Monotony is a measure related to the oscillation of the training load in a given period. According to Freitas et al. (2015), monotony values above 2.0 AU pertain to slight variation in training loads and can provide negative adaptations to training such as decreased performance, increased infectious diseases, and injuries in athletes. Thus, the monotony analyzed in the present study shows that even at the time of training (higher loads), the loads were well distributed during the week, with oscillations and recovery periods, which may reflect positive adaptations to the training.

The mean height of the CMJ has been characterized as a highly very reliable measure for monitoring neuromuscular status (Claudino et al., 2017). Previous studies used the measurement of the highest jump to monitor training responses in volleyball (Freitas et al., 2014) and beach volleyball (Oliveira et al., 2018); the two showed no differences throughout the study, similar to what was presented in this study even using the CMJ mean. Freitas et al. (2014), expected a reduction in jump height due to the increase in the number of eccentric actions. The authors justified the lack of sensitivity of the measure with the low training load that could cause loss of muscle function. In our study, one could perhaps imagine that when using the average of the jumps, some difference could be observed; however, as already mentioned, these statistical differences were not observed. According to Carroll et al. (2019) the high reliability of the mean height of the jumps makes a more solidified change in the physiological state necessary. Therefore, it is an excellent measure with analyzes that better reflect the athlete’s adapted state, for example, the smallest worthwhile change (SWC).

Furthermore, Pelzer et al. (2020) demonstrated that jump’s high volume in a beach volleyball training did not trigger responses in reducing mean height of jump test before and after training. However, moderate (80 jumps) and low volume (40 jumps) jumping sessions accompanied by changes of direction and dips caused fatigue neuromuscular (Pelzer et al., 2020). It appears that jumper specificity for volleyball and beach volleyball athletes leads to excellent resistance and jumping ability. In our study, when comparing pre-and post-training times, there were no differences for CMJ. These results corroborate with Pelzer et al. (2020) on maintaining jump height even after training and game. For these athletes, the training somehow serves as a post-activation potentiation mechanism or reveals a low state of fatigue (Freitas et al., 2014).

This study has some limitations such as: a) the lack of monitoring of the occurrence of injuries and respiratory infections, usually associated with overtraining, b) the number of athletes is small and the conclusions of this study deserve caution and c) there may have been greater variability in jump height between the athletes and there was no correlation between the times of jump.

CONCLUSION

We conclude that the changes in psychophysiological and neuromuscular parameters were similar between blockers and defenders and the training loads evaluated by TRIMP, monotony, total weekly training load, daily training load were well distributed with increases in the first two weeks before the competition and reduced training loads during and after the competition. The monotony values highlight a good distribution of these loads throughout the mesocycle. In addition, the similar values of TRIMP and RPE reveal that these measures represent an exciting construct. The beach volleyball athletes in our study have a high capacity to maintain HRV and CMJ height during different moments and imposed training loads. Analyzing them together can bring information that helps better explain the load monitoring responses. Future studies should aim to the competition outcome, win/lost effectivity and association within the loading and change in markers across the weeks before competition and also investigate association within the work to rest ratio, because different number of rallies and their length may also change the time of the match and players overal internal and external loading.

ACKNOWLEDGEMENTS

Thank you to all beach volleyball players.

• FUNDING
  This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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Publication Dates

• Publication in this collection
  17 Mar 2025
• Date of issue
  2025

History

• Received
  18 Dec 2023
• Accepted
  03 Jan 2025